model update

README.md

@@ -2,7 +2,7 @@
 datasets:
 - relbert/semeval2012_relational_similarity
 model-index:
-- name: relbert/roberta-large-semeval2012-mask-prompt-e-nce_logout-classification
+- name: relbert/roberta-large-semeval2012-mask-prompt-e-nce-classification-conceptnet-validated
   results:
   - task:
       name: Relation Mapping
@@ -14,7 +14,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9020833333333333
+      value: 0.812936507936508
   - task:
       name: Analogy Questions (SAT full)
       type: multiple-choice-qa
@@ -153,27 +153,27 @@ model-index:
       value: 0.8931476213358844
 
 ---
-# relbert/roberta-large-semeval2012-mask-prompt-e-nce_logout-classification
+# relbert/roberta-large-semeval2012-mask-prompt-e-nce-classification-conceptnet-validated
 
 RelBERT fine-tuned from [roberta-large](https://huggingface.co/roberta-large) on  
 [relbert/semeval2012_relational_similarity](https://huggingface.co/datasets/relbert/semeval2012_relational_similarity).
 Fine-tuning is done via [RelBERT](https://github.com/asahi417/relbert) library (see the repository for more detail).
 It achieves the following results on the relation understanding tasks:
-- Analogy Question ([dataset](https://huggingface.co/datasets/relbert/analogy_questions), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-mask-prompt-e-nce_logout-classification/raw/main/analogy.json)):
+- Analogy Question ([dataset](https://huggingface.co/datasets/relbert/analogy_questions), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-mask-prompt-e-nce-classification-conceptnet-validated/raw/main/analogy.json)):
     - Accuracy on SAT (full): 0.5320855614973262 
     - Accuracy on SAT: 0.5370919881305638
     - Accuracy on BATS: 0.67982212340189
     - Accuracy on U2: 0.5526315789473685
     - Accuracy on U4: 0.5393518518518519
     - Accuracy on Google: 0.808
-- Lexical Relation Classification ([dataset](https://huggingface.co/datasets/relbert/lexical_relation_classification), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-mask-prompt-e-nce_logout-classification/raw/main/classification.json)):
+- Lexical Relation Classification ([dataset](https://huggingface.co/datasets/relbert/lexical_relation_classification), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-mask-prompt-e-nce-classification-conceptnet-validated/raw/main/classification.json)):
     - Micro F1 score on BLESS: 0.9199939731806539
     - Micro F1 score on CogALexV: 0.8643192488262911
     - Micro F1 score on EVALution: 0.6944745395449621
     - Micro F1 score on K&H+N: 0.9670306739931835
     - Micro F1 score on ROOT09: 0.8909432779692886
-- Relation Mapping ([dataset](https://huggingface.co/datasets/relbert/relation_mapping), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-mask-prompt-e-nce_logout-classification/raw/main/relation_mapping.json)):
-    - Accuracy on Relation Mapping: 0.9020833333333333 
+- Relation Mapping ([dataset](https://huggingface.co/datasets/relbert/relation_mapping), [full result](https://huggingface.co/relbert/roberta-large-semeval2012-mask-prompt-e-nce-classification-conceptnet-validated/raw/main/relation_mapping.json)):
+    - Accuracy on Relation Mapping: 0.812936507936508 
 
 
 ### Usage
@@ -184,7 +184,7 @@ pip install relbert
 and activate model as below.
 ```python
 from relbert import RelBERT
-model = RelBERT("relbert/roberta-large-semeval2012-mask-prompt-e-nce_logout-classification")
+model = RelBERT("relbert/roberta-large-semeval2012-mask-prompt-e-nce-classification-conceptnet-validated")
 vector = model.get_embedding(['Tokyo', 'Japan'])  # shape of (1024, )
 ```
 
@@ -216,7 +216,7 @@ The following hyperparameters were used during training:
  - n_sample: 640
  - gradient_accumulation: 8
 
-The full configuration can be found at [fine-tuning parameter file](https://huggingface.co/relbert/roberta-large-semeval2012-mask-prompt-e-nce_logout-classification/raw/main/trainer_config.json).
+The full configuration can be found at [fine-tuning parameter file](https://huggingface.co/relbert/roberta-large-semeval2012-mask-prompt-e-nce-classification-conceptnet-validated/raw/main/trainer_config.json).
 
 ### Reference
 If you use any resource from RelBERT, please consider to cite our [paper](https://aclanthology.org/2021.eacl-demos.7/).

relation_mapping.json

@@ -0,0 +1 @@
+{"accuracy": 0.812936507936508, "prediction": [{"source": ["solar system", "sun", "planet", "mass", "attracts", "revolves", "gravity"], "true": ["atom", "nucleus", "electron", "charge", "attracts", "revolves", "electromagnetism"], "pred": ["atom", "nucleus", "electron", "charge", "attracts", "revolves", "electromagnetism"], "alignment_match": true, "accuracy": 1, "similarity": 0.9999999004005095, "similarity_true": 0.9999999004005095}, {"source": ["water", "flows", "pressure", "water tower", "bucket", "filling", "emptying", "hydrodynamics"], "true": ["heat", "transfers", "temperature", "burner", "kettle", "heating", "cooling", "thermodynamics"], "pred": ["heat", "transfers", "temperature", "burner", "kettle", "heating", "cooling", "thermodynamics"], "alignment_match": true, "accuracy": 1, "similarity": 0.9732432851288162, "similarity_true": 0.9732432851288162}, {"source": ["waves", "shore", "reflects", "water", "breakwater", "rough", "calm", "crashing"], "true": ["sounds", "wall", "echoes", "air", "insulation", "loud", "quiet", "vibrating"], "pred": ["sounds", "wall", "echoes", "air", "insulation", "loud", "quiet", "vibrating"], "alignment_match": true, "accuracy": 1, "similarity": 0.9545210819824754, "similarity_true": 0.9545210819824754}, {"source": ["combustion", "fire", "fuel", "burning", "hot", "intense", "oxygen", "carbon dioxide"], "true": ["respiration", "animal", "food", "breathing", "living", "vigorous", "oxygen", "carbon dioxide"], "pred": ["respiration", "animal", "food", "breathing", "living", "vigorous", "oxygen", "carbon dioxide"], "alignment_match": true, "accuracy": 1, "similarity": 0.9999998999750961, "similarity_true": 0.9999998999750961}, {"source": ["sound", "low", "high", "echoes", "loud", "quiet", "horn"], "true": ["light", "red", "violet", "reflects", "bright", "dim", "lens"], "pred": ["light", "red", "violet", "reflects", "bright", "dim", "lens"], "alignment_match": true, "accuracy": 1, "similarity": 0.9599179876097158, "similarity_true": 0.9599179876097158}, {"source": ["projectile", "trajectory", "earth", "parabolic", "air", "gravity", "attracts"], "true": ["planet", "orbit", "sun", "elliptical", "space", "gravity", "attracts"], "pred": ["sun", "orbit", "planet", "elliptical", "space", "gravity", "attracts"], "alignment_match": false, "accuracy": 0.7142857142857143, "similarity": 0.9999999004523795, "similarity_true": 0.9999999004523795}, {"source": ["breeds", "selection", "conformance", "artificial", "popularity", "breeding", "domesticated"], "true": ["species", "competition", "adaptation", "natural", "fitness", "mating", "wild"], "pred": ["species", "adaptation", "fitness", "natural", "competition", "mating", "wild"], "alignment_match": false, "accuracy": 0.5714285714285714, "similarity": 0.9552215237577313, "similarity_true": 0.9296904979284729}, {"source": ["ball", "billiards", "speed", "table", "bouncing", "moving", "slow", "fast"], "true": ["molecules", "gas", "temperature", "container", "pressing", "moving", "cold", "hot"], "pred": ["gas", "molecules", "temperature", "container", "pressing", "moving", "cold", "hot"], "alignment_match": false, "accuracy": 0.75, "similarity": 0.946192571433233, "similarity_true": 0.946192571433233}, {"source": ["computer", "processing", "erasing", "write", "read", "memory", "outputs", "inputs", "bug"], "true": ["mind", "thinking", "forgetting", "memorize", "remember", "memory", "muscles", "senses", "mistake"], "pred": ["mind", "thinking", "forgetting", "memorize", "remember", "memory", "senses", "muscles", "mistake"], "alignment_match": false, "accuracy": 0.7777777777777778, "similarity": 0.9434501460511003, "similarity_true": 0.9434501460511003}, {"source": ["slot machines", "reels", "spinning", "winning", "losing"], "true": ["bacteria", "genes", "mutating", "reproducing", "dying"], "pred": ["bacteria", "genes", "mutating", "reproducing", "dying"], "alignment_match": true, "accuracy": 1, "similarity": 0.9218006272286946, "similarity_true": 0.9218006272286946}, {"source": ["war", "soldier", "destroy", "fighting", "defeat", "attacks", "weapon"], "true": ["argument", "debater", "refute", "arguing", "acceptance", "criticizes", "logic"], "pred": ["logic", "debater", "refute", "arguing", "acceptance", "criticizes", "argument"], "alignment_match": false, "accuracy": 0.7142857142857143, "similarity": 0.9272307593794461, "similarity_true": 0.9272307593794461}, {"source": ["buyer", "merchandise", "buying", "selling", "returning", "valuable", "worthless"], "true": ["believer", "belief", "accepting", "advocating", "rejecting", "true", "false"], "pred": ["believer", "belief", "advocating", "rejecting", "accepting", "false", "true"], "alignment_match": false, "accuracy": 0.2857142857142857, "similarity": 0.9428603532764525, "similarity_true": 0.9334176290665042}, {"source": ["foundations", "buildings", "supporting", "solid", "weak", "crack"], "true": ["reasons", "theories", "confirming", "rational", "dubious", "flaw"], "pred": ["reasons", "theories", "confirming", "rational", "dubious", "flaw"], "alignment_match": true, "accuracy": 1, "similarity": 0.9155279210436017, "similarity_true": 0.9155279210436017}, {"source": ["obstructions", "destination", "route", "traveller", "traveling", "companion", "arriving"], "true": ["difficulties", "goal", "plan", "person", "problem solving", "partner", "succeeding"], "pred": ["difficulties", "goal", "plan", "person", "problem solving", "partner", "succeeding"], "alignment_match": true, "accuracy": 1, "similarity": 0.887969695538646, "similarity_true": 0.887969695538646}, {"source": ["money", "allocate", "budget", "effective", "cheap", "expansive"], "true": ["time", "invest", "schedule", "efficient", "quick", "slow"], "pred": ["time", "invest", "schedule", "efficient", "quick", "slow"], "alignment_match": true, "accuracy": 1, "similarity": 0.9430343394486328, "similarity_true": 0.9430343394486328}, {"source": ["seeds", "planted", "fruitful", "fruit", "grow", "wither", "blossom"], "true": ["ideas", "inspired", "productive", "product", "develop", "fail", "succeed"], "pred": ["ideas", "succeed", "productive", "product", "develop", "fail", "inspired"], "alignment_match": false, "accuracy": 0.7142857142857143, "similarity": 0.9517706158743442, "similarity_true": 0.9517706158743442}, {"source": ["machine", "working", "turned on", "turned off", "broken", "power", "repair"], "true": ["mind", "thinking", "awake", "asleep", "confused", "intelligence", "therapy"], "pred": ["mind", "awake", "thinking", "asleep", "confused", "intelligence", "therapy"], "alignment_match": false, "accuracy": 0.7142857142857143, "similarity": 0.9264438485891653, "similarity_true": 0.9058145540365795}, {"source": ["object", "hold", "weight", "heavy", "light"], "true": ["idea", "understand", "analyze", "important", "trivial"], "pred": ["idea", "analyze", "understand", "important", "trivial"], "alignment_match": false, "accuracy": 0.6, "similarity": 0.9235133624327503, "similarity_true": 0.9235133624327503}, {"source": ["follow", "leader", "path", "follower", "lost", "wanders", "twisted", "straight"], "true": ["understand", "speaker", "argument", "listener", "misunderstood", "digresses", "complicated", "simple"], "pred": ["misunderstood", "speaker", "argument", "listener", "understand", "digresses", "complicated", "simple"], "alignment_match": false, "accuracy": 0.75, "similarity": 0.9500788422682184, "similarity_true": 0.9434717346199709}, {"source": ["seeing", "light", "illuminating", "darkness", "view", "hidden"], "true": ["understanding", "knowledge", "explaining", "confusion", "interpretation", "secret"], "pred": ["explaining", "knowledge", "understanding", "confusion", "interpretation", "secret"], "alignment_match": false, "accuracy": 0.6666666666666666, "similarity": 0.9057748419214778, "similarity_true": 0.9023808021740224}]}